OpenRaiser/Intern-Atlas huggingface dataset:
Analysis of a Statistical Hypothesis Based Learning Mechanism for Faster crawling
Venue: arXiv cs.LG 2012
Year: 2012

The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of crawling process in a search engine. A search engine handles a lot of queries from various parts of this world, and the answers of it solely depend on the knowledge that it gathers by means of crawling. The information sharing becomes a most common habit of the society, and it is done by means of publishing structured, semi-structured and unstructured resources on the web. This social practice leads to an exponential growth of web-resource, and hence it became essential to crawl for continuous updating of web-knowledge and modification of several existing resources in any situation. In this paper one statistical hypothesis based learning mechanism is incorporated for learning the behavior of crawling speed in different environment of network, and for intelligently control of the speed of crawler. The scaling technique is used to compare the performance proposed method with the standard crawler. The high speed performance is observed after scaling, and the retrieval of relevant web-resource in such a high speed is analyzed.
Fast Adaptive S-ALOHA Scheme for Event-driven M2M Communications (Journal version)
Venue: arXiv cs.IT 2012
Year: 2012

Supporting massive device transmission is challenging in Machine-to-Machine (M2M) communications. Particularly, in event-driven M2M communications, a large number of devices activate within a short period of time, which in turn causes high radio congestions and severe access delay. To address this issue, we propose a Fast Adaptive S-ALOHA (FASA) scheme for random access control of M2M communication systems with bursty traffic. Instead of the observation in a single slot, the statistics of consecutive idle and collision slots are used in FASA to accelerate the tracking process of network status which is critical for optimizing S-ALOHA systems. Using drift analysis, we design the FASA scheme such that the estimate of the backlogged devices converges fast to the true value. Furthermore, by examining the $T$-slot drifts, we prove that the proposed FASA scheme is stable as long as the average arrival rate is smaller than $e^{-1}$, in the sense that the Markov Chain derived from the scheme is geometrically ergodic. Simulation results demonstrate that the proposed FASA scheme outperforms traditional additive schemes such as PB-ALOHA and achieves near-optimal performance in reducing access delay. Moreover, compared to multiplicative schemes, FASA shows its robustness under heavy traffic load in addition to better delay performance.
LP Rounding for k-Centers with Non-uniform Hard Capacities
Venue: arXiv cs.DS 2012
Year: 2012

In this paper we consider a generalization of the classical k-center problem with capacities. Our goal is to select k centers in a graph, and assign each node to a nearby center, so that we respect the capacity constraints on centers. The objective is to minimize the maximum distance a node has to travel to get to its assigned center. This problem is NP-hard, even when centers have no capacity restrictions and optimal factor 2 approximation algorithms are known. With capacities, when all centers have identical capacities, a 6 approximation is known with no better lower bounds than for the infinite capacity version. While many generalizations and variations of this problem have been studied extensively, no progress was made on the capacitated version for a general capacity function. We develop the first constant factor approximation algorithm for this problem. Our algorithm uses an LP rounding approach to solve this problem, and works for the case of non-uniform hard capacities, when multiple copies of a node may not be chosen and can be extended to the case when there is a hard bound on the number of copies of a node that may be selected. In addition we establish a lower bound on the integrality gap of 7(5) for non-uniform (uniform) hard capacities. In addition we prove that if there is a (3-eps)-factor approximation for this problem then P=NP. Finally, for non-uniform soft capacities we present a much simpler 11-approximation algorithm, which we find as one more evidence that hard capacities are much harder to deal with.
Variance based Scheduling to Improve the QoS Performance at the Cell Edge
Venue: arXiv cs.NI 2012
Year: 2012

Now a days mobile phones are most often used for data communication rather than voice calls. Due to this change in user behavior, there is a need to improve the QoS received by the user. One of the ways of improving the QoS is an efficient scheduling algorithm which incorporates the needs of the users and variation in channel condition. The parameters used to measure the efficiency of the scheduling algorithms are the Jain Fairness Index and the overall system throughput. In this paper we have proposed a variance based scheduling algorithm which selects the user who has the highest variance of data transmitted in a given time frame as a parameter for scheduling. This ensures that eventually, the users transmit almost equal amounts of data regardless of channel condition. The simulation results shows that the proposed algorithm achieves high Jain Fairness Index of 0.92 with a lesser drop in the system throughput 18% as compared to Dynamically altering Proportionally Fair Algorithm's 20% using the Proportionally Fair Algorithm as reference.
Modeling Network Coded TCP: Analysis of Throughput and Energy Cost
Venue: arXiv cs.NI 2012
Year: 2012

We analyze the performance of TCP and TCP with network coding (TCP/NC) in lossy networks. We build upon the framework introduced by Padhye et al. and characterize the throughput behavior of classical TCP and TCP/NC as a function of erasure probability, round-trip time, maximum window size, and duration of the connection. Our analytical results show that network coding masks random erasures from TCP, thus preventing TCP's performance degradation in lossy networks. It is further seen that TCP/NC has significant throughput gains over TCP. In addition, we show that TCP/NC may lead to cost reduction for wireless network providers while maintaining a certain quality of service to their users. We measure the cost in terms of number of base stations, which is highly correlated to the energy, capital, and operational costs of a network provider. We show that increasing the available bandwidth may not necessarily lead to increase in throughput, particularly in lossy networks in which TCP does not perform well. We show that using protocols such as TCP/NC, which are more resilient to erasures, may lead to a throughput commensurate the bandwidth dedicated to each user.
AES-CBC Software Execution Optimization
Venue: arXiv cs.CR 2012
Year: 2012

With the proliferation of high-speed wireless networking, the necessity for efficient, robust and secure encryption modes is ever increasing. But, cryptography is primarily a computationally intensive process. This paper investigates the performance and efficiency of IEEE 802.11i approved Advanced Encryption Standard (AES)-Rijndael ciphering/deciphering software in Cipher Block Chaining (CBC) mode. Simulations are used to analyse the speed, resource consumption and robustness of AES-CBC to investigate its viability for image encryption usage on common low power devices. The detailed results presented in this paper provide a basis for performance estimation of AES cryptosystems implemented on wireless devices. The use of optimized AES-CBC software implementation gives a superior encryption speed performance by 12 - 30%, but at the cost of twice more memory for code size.
Analytical Solution for the Generalized Fermat-Torricelli Problem
Venue: arXiv cs.CG 2012
Year: 2012

We present explicit analytical solution for the problem of minimization of the function $ F(x,y)= \sum_{j=1}^3 m_j \sqrt{(x-x_j)^2+(y-y_j)^2} $, i.e. we find the coordinates of stationary point and the corresponding critical value of $ F(x,y) $ as functions of $ {m_j,x_j,y_j}_{j=1}^3 $. In addition, we also discuss inverse problem of finding such values of $ m_1,m_2,m_3 $ with the aim for the corresponding function $ F $ to posses a prescribed position of stationary point.
First steps in synthetic guarded domain theory: step-indexing in the topos of trees
Venue: arXiv cs.LO 2012
Year: 2012

We present the topos S of trees as a model of guarded recursion. We study the internal dependently-typed higher-order logic of S and show that S models two modal operators, on predicates and types, which serve as guards in recursive definitions of terms, predicates, and types. In particular, we show how to solve recursive type equations involving dependent types. We propose that the internal logic of S provides the right setting for the synthetic construction of abstract versions of step-indexed models of programming languages and program logics. As an example, we show how to construct a model of a programming language with higher-order store and recursive types entirely inside the internal logic of S. Moreover, we give an axiomatic categorical treatment of models of synthetic guarded domain theory and prove that, for any complete Heyting algebra A with a well-founded basis, the topos of sheaves over A forms a model of synthetic guarded domain theory, generalizing the results for S.
Calculations of Frequency Response Functions (FRF) Using Computer Smart Office Software and Nyquist Plot under Gyroscopic Effect Rotation
Venue: arXiv cs.CE 2012
Year: 2012

Regenerated (FRF curves), synthesis of (FRF) curves there are two main requirement in the form of response model, The first being that of regenerating "Theoretical" curve for the frequency response function actually measured and analysis and the second being that of synthesising the other functions which were not measured,(FRF) that isolates the inherent dynamic properties of a mechanical structure. Experimental modal parameters (frequency, damping, and mode shape) are also obtained from a set of (FRF) measurements. The (FRF) describes the input-output relationship between two points on a structure as a function of frequency. Therefore, an (FRF) is actually defined between a single input DOF (point & direction), and a single output (DOF), although the FRF was previously defined as a ratio of the Fourier transforms of an output and input signal. In this paper we detection FRF curve using Nyquist plot under gyroscopic effect in revolving structure using computer smart office software. Keywords - FRF curve; modal test; Nyquist plot; software engineering; gyroscopic effect; smart office.
Image Super-Resolution via Dual-Dictionary Learning And Sparse Representation
Venue: arXiv cs.CV 2012
Year: 2012

Learning-based image super-resolution aims to reconstruct high-frequency (HF) details from the prior model trained by a set of high- and low-resolution image patches. In this paper, HF to be estimated is considered as a combination of two components: main high-frequency (MHF) and residual high-frequency (RHF), and we propose a novel image super-resolution method via dual-dictionary learning and sparse representation, which consists of the main dictionary learning and the residual dictionary learning, to recover MHF and RHF respectively. Extensive experimental results on test images validate that by employing the proposed two-layer progressive scheme, more image details can be recovered and much better results can be achieved than the state-of-the-art algorithms in terms of both PSNR and visual perception.
On the Use of Latency Graphs for the Construction of Tor Circuits
Venue: arXiv cs.CR 2012
Year: 2012

The use of anonymity-based infrastructures and anonymisers is a plausible solution to mitigate privacy problems on the Internet. Tor (short for The onion router) is a popular low-latency anonymity system that can be installed as an end-user application on a wide range of operating systems to redirect the traffic through a series of anonymising proxy circuits. The construction of these circuits determines both the latency and the anonymity degree of the Tor anonymity system. While some circuit construction strategies lead to delays which are tolerated for activities like Web browsing, they can make the system vulnerable to linking attacks. We evaluate in this paper three classical strategies for the construction of Tor circuits, with respect to their de-anonymisation risk and latency performance. We then develop a new circuit selection algorithm that considerably reduces the success probability of linking attacks while keeping a good degree of performance. We finally conduct experiments on a real-world Tor deployment over PlanetLab. Our experimental results confirm the validity of our strategy and its performance increase for Web browsing.
A Novel Overlay IDS For Wireless Sensor Networks
Venue: arXiv cs.CR 2012
Year: 2012

Wireless Sensor Network (WSN) consists of low cost sensor nodes which cannot afford to implement sophisticated security system in it. That is why intrusion detection architecture for WSN is considerably different and difficult to implement. Most of the current implementations are based on exchanging anomaly signals among the leaf level sensors resulting in too much power consumption. We propose a novel architecture for Intrusion Detection System (IDS) in WSN based on Hierarchical Overlay Design (HOD) that will distribute the overall responsibility of intrusion detection into entities and thus conserve memory and power of the nodes. The architecture uses layered design with GSM cell like structure based on special monitor nodes. The HOD structure enables the sensors to communicate using far less messages and thus conserve precious power and also saves memory by not implementing IDS module on each sensor. The proposal also uses rippling of alarm through layers and thus ensures proper delivery to the uppermost layer with redundancy.
Hardy-Schatten Norms of Systems, Output Energy Cumulants and Linear Quadro-Quartic Gaussian Control
Venue: arXiv cs.SY 2012
Year: 2012

This paper is concerned with linear stochastic control systems in state space. The integral of the squared norm of the system output over a bounded time interval is interpreted as energy. The cumulants of the output energy in the infinite-horizon limit are related to Schatten norms of the system in the Hardy space of transfer functions and the risk-sensitive performance index. We employ a novel performance criterion which seeks to minimize a combination of the average value and the variance of the output energy of the system per unit time. The resulting linear quadro-quartic Gaussian control problem involves the H2 and H4-norms of the closed-loop system. We obtain equations for the optimal controller and outline a homotopy method which reduces the solution of the problem to the numerical integration of a differential equation initialized by the standard linear quadratic Gaussian controller.
Analysis of parametric biological models with non-linear dynamics
Venue: arXiv cs.CE 2012
Year: 2012

In this paper we present recent results on parametric analysis of biological models. The underlying method is based on the algorithms for computing trajectory sets of hybrid systems with polynomial dynamics. The method is then applied to two case studies of biological systems: one is a cardiac cell model for studying the conditions for cardiac abnormalities, and the second is a model of insect nest-site choice.
A subsystems approach for parameter estimation of ODE models of hybrid systems
Venue: arXiv cs.CE 2012
Year: 2012

We present a new method for parameter identification of ODE system descriptions based on data measurements. Our method works by splitting the system into a number of subsystems and working on each of them separately, thereby being easily parallelisable, and can also deal with noise in the observations.
Statistical Model Checking for Stochastic Hybrid Systems
Venue: arXiv cs.CE 2012
Year: 2012

This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming from systems biology and energy aware buildings.
A GPU-accelerated Branch-and-Bound Algorithm for the Flow-Shop Scheduling Problem
Venue: arXiv cs.DC 2012
Year: 2012

Branch-and-Bound (B&B) algorithms are time intensive tree-based exploration methods for solving to optimality combinatorial optimization problems. In this paper, we investigate the use of GPU computing as a major complementary way to speed up those methods. The focus is put on the bounding mechanism of B&B algorithms, which is the most time consuming part of their exploration process. We propose a parallel B&B algorithm based on a GPU-accelerated bounding model. The proposed approach concentrate on optimizing data access management to further improve the performance of the bounding mechanism which uses large and intermediate data sets that do not completely fit in GPU memory. Extensive experiments of the contribution have been carried out on well known FSP benchmarks using an Nvidia Tesla C2050 GPU card. We compared the obtained performances to a single and a multithreaded CPU-based execution. Accelerations up to x100 are achieved for large problem instances.
Dynamic Anomalography: Tracking Network Anomalies via Sparsity and Low Rank
Venue: arXiv cs.NI 2012
Year: 2012

In the backbone of large-scale networks, origin-to-destination (OD) traffic flows experience abrupt unusual changes known as traffic volume anomalies, which can result in congestion and limit the extent to which end-user quality of service requirements are met. As a means of maintaining seamless end-user experience in dynamic environments, as well as for ensuring network security, this paper deals with a crucial network monitoring task termed dynamic anomalography. Given link traffic measurements (noisy superpositions of unobserved OD flows) periodically acquired by backbone routers, the goal is to construct an estimated map of anomalies in real time, and thus summarize the network `health state' along both the flow and time dimensions. Leveraging the low intrinsic-dimensionality of OD flows and the sparse nature of anomalies, a novel online estimator is proposed based on an exponentially-weighted least-squares criterion regularized with the sparsity-promoting $\ell_1$-norm of the anomalies, and the nuclear norm of the nominal traffic matrix. After recasting the non-separable nuclear norm into a form amenable to online optimization, a real-time algorithm for dynamic anomalography is developed and its convergence established under simplifying technical assumptions. For operational conditions where computational complexity reductions are at a premium, a lightweight stochastic gradient algorithm based on Nesterov's acceleration technique is developed as well. Comprehensive numerical tests with both synthetic and real network data corroborate the effectiveness of the proposed online algorithms and their tracking capabilities, and demonstrate that they outperform state-of-the-art approaches developed to diagnose traffic anomalies.
Anisotropic Norm Bounded Real Lemma for Linear Discrete Time Varying Systems
Venue: arXiv cs.SY 2012
Year: 2012

We consider a finite horizon linear discrete time varying system whose input is a random noise with an imprecisely known probability law. The statistical uncertainty is described by a nonnegative parameter a which constrains the anisotropy of the noise as an entropy theoretic measure of deviation of the actual noise distribution from Gaussian white noise laws with scalar covariance matrices. The worst-case disturbance attenuation capabilities of the system with respect to the statistically uncertain random inputs are quantified by the a-anisotropic norm which is an appropriately constrained operator norm of the system. We establish an anisotropic norm bounded real lemma which provides a state-space criterion for the a-anisotropic norm of the system not to exceed a given threshold. The criterion is organized as an inequality on the determinants of matrices associated with a difference Riccati equation and extends the Bounded Real Lemma of the H-infinity-control theory. We also provide a necessary background on the anisotropy-based robust performance analysis.
Semi-supervised Clustering Ensemble by Voting
Venue: arXiv cs.LG 2012
Year: 2012

Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of the same clustering algorithm for the same data set, this is accomplished using on a consensus function, the efficiency and accuracy of this method has been proven in many works in literature. In the first part of this paper we make a comparison among current approaches to clustering ensemble in literature. All of these approaches consist of two main steps: the ensemble generation and consensus function. In the second part of the paper, we suggest engaging supervision in the clustering ensemble procedure to get more enhancements on the clustering results. Supervision can be applied in two places: either by using semi-supervised algorithms in the clustering ensemble generation step or in the form of a feedback used by the consensus function stage. Also, we introduce a flexible two parameter weighting mechanism, the first parameter describes the compatibility between the datasets under study and the semi-supervised clustering algorithms used to generate the base partitions, the second parameter is used to provide the user feedback on the these partitions. The two parameters are engaged in a "relabeling and voting" based consensus function to produce the final clustering.
Can the Elephants Handle the NoSQL Onslaught?
Venue: arXiv cs.DB 2012
Year: 2012

In this new era of "big data", traditional DBMSs are under attack from two sides. At one end of the spectrum, the use of document store NoSQL systems (e.g. MongoDB) threatens to move modern Web 2.0 applications away from traditional RDBMSs. At the other end of the spectrum, big data DSS analytics that used to be the domain of parallel RDBMSs is now under attack by another class of NoSQL data analytics systems, such as Hive on Hadoop. So, are the traditional RDBMSs, aka "big elephants", doomed as they are challenged from both ends of this "big data" spectrum? In this paper, we compare one representative NoSQL system from each end of this spectrum with SQL Server, and analyze the performance and scalability aspects of each of these approaches (NoSQL vs. SQL) on two workloads (decision support analysis and interactive data-serving) that represent the two ends of the application spectrum. We present insights from this evaluation and speculate on potential trends for the future.